%INTEGRAL  Calculates the integral of an image
%
%     s = cv.integral(src)
%     [s, sqsum, tilted] = cv.integral(src)
%     [...] = cv.integral(src, 'OptionName',optionValue, ...)
%
% ## Input
% * __src__ Source image as `W x H`, 8-bit, 16-bit or floating-point
%   (`single` or `double`).
%
% ## Output
% * __s__ Integral image as `(W+1) x (H+1)`, 32-bit integer or floating-point
%   (`single` or `double`).
% * __sqsum__ Integral image for squared pixel values. It is `(W+1) x (H+1)`,
%   double-precision floating-point array.
% * __tilted__ Integral for the image rotated by 45 degrees. It is
%   `(W+1) x (H+1)` array with the same data type as `s`.
%
% ## Options
% * __SDepth__ desired depth of the integral and the tilted integral images,
%   `int32`, `single`, or `double`. default -1
% * __SQDepth__ desired depth of the integral image of squared pixel values,
%   `single` or `double`. default -1
%
% The function calculates one or more integral images for the source image as
% follows:
%
%     s(X,Y) = sum_{x<X,y<Y} src(x,y)
%     sqsum(X,Y) = sum_{x<X,y<Y} src(x,y)^2
%     tilted(X,Y) = sum_{y<Y,abs(x-X+1)<=Y-y-1} src(x,y)
%
% Using these integral images, you can calculate sum, mean, and standard
% deviation over a specific up-right or rotated rectangular region of the
% image in a constant time, for example:
%
%     sum_{x_1 <= x < x_2, y_1 <= y < y_2} src(x,y)
%         = s(x_2, y_2) - s(x_1, y_2) - s(x_2, y_1) + s(x_1, y_1)
%
% It makes possible to do a fast blurring or fast block correlation with a
% variable window size, for example. In case of multi-channel images, sums for
% each channel are accumulated independently.
%
% See also: integralImage
%
